- Company Name
- Micropep Technologies
- Job Title
- Senior AI Scientist (W/M)
- Job Description
-
**Job Title:** Senior AI Scientist (W/M)
**Role Summary:**
Lead the development and industrialisation of AI-driven peptide discovery solutions. Design predictive models, oversee data pipelines, and serve as the internal and external AI expert, aligning research outcomes with product strategy.
**Expectations:**
- Deliver end‑to‑end ML/DL pipelines that predict peptide properties and guide in‑silico design.
- Mentor cross‑functional teams on AI best practices.
- Represent the company at academic and industry forums, ensuring cutting‑edge methods are adopted.
- Maintain rigorous scientific standards and reproducible workflows.
**Key Responsibilities:**
- **Model Development:** Train, optimise and evaluate transformers, protein‑specific LLMs, autoencoders, VAEs, GNNs, and other modern architectures for classification, regression and embedding tasks on biological datasets.
- **Data Engineering:** Define data structuring, preprocessing, bias assessment, and quality checks in collaboration with data‑engineering staff.
- **In‑silico Peptide Design:** Translate model outputs into biologically viable peptide candidates, integrating experimental, regulatory and IP constraints.
- **MLOps & Industrialisation:** Build scalable, reproducible pipelines using CI/CD, Docker, and cloud services; ensure data integrity and model governance.
- **Strategic Leadership:** Act as technology business partner to scientists and executives; evangelise AI solutions; shape the AI roadmap; monitor emerging AI research for strategic advantage.
- **External Collaboration:** Lead partnerships with academia and technology firms; produce clear, scientifically robust reports and presentations.
**Required Skills:**
- Deep expertise in ML/DL (cross‑validation, hyper‑parameter optimisation, pipeline construction).
- Proficiency with transformers, autoencoders, VAEs, GNNs, and protein‑specific LLMs.
- Strong data‑engineering capabilities: data cleaning, structuring, exploratory analysis, and database management.
- Bioinformatics acumen: understanding of biological datasets, peptide chemistry, sequence embeddings, and structural biology.
- Cloud computing knowledge (AWS, GCP, Azure).
- Scientific rigor: reproducible research, meticulous documentation, and ability to synthesize advanced literature.
- Excellent communication and pedagogical skills; ability to translate complex concepts to non‑technical stakeholders.
**Required Education & Certifications:**
- PhD or Master’s degree in Computer Science, Machine Learning, Bioinformatics, Computational Biology, or a closely related field.
- Proven track record of ML/DL publications or patents is highly desirable.
- Certifications in cloud platforms or AI frameworks are a plus.